The role of first-trimester single arterial vessel sign instead of a V-sign at the level of the three-vessel and tracheal view in screening for congenital heart diseases
Bibliographic record
Abstract
Introduction: Despite efforts from dedicated societies, prenatal detection rates (DRs) of congenital heart diseases (CHDs) remain unsatisfactory.Early cardiac scan is believed to play an important role in selecting fetuses for further assessment and to improve the DRs.The aims of the study were to compare first-trimester cardiac parameters and follow-up fetal, postnatal echocardiography and autopsy findings in fetuses presenting the single arterial vessel with fetuses presenting the "V-sign" at the level of the 3 vessels and trachea view in colour mapping (3VTVc), and to measure screening performance of the single arterial vessel in 3VTV for D-TGA and D-TGA+VSD, all CHDs, and ductal-dependent (DD) CHDs.Material and methods: This study was a prospective observational analysis that covered 2338 pregnancy referrals.Study protocol included an early fetal echocardiography approach to the 4-chamber view in colour mapping and 3VTVc.Results: Among single arterial vessel fetuses 2 normal hearts, 66 CHDs, including 42 DD lesions, were identified; and among "V-sign" fetuses, 1913 normal hearts, 42 CHDs, including 2 DD lesions.The single arterial vessel sign was highly sensitive (93.3%) and specific (97.3%) for D-TGA/D-TGA+VSD at the time of the early cardiac scan.Moreover, the single arterial vessel in 3VTV was highly sensitive (95.8%) and specific (98.8%) for other ductal-dependent CHDs.Conclusions: Differentiation between the single arterial vessel sign in 3VTV and the "V-sign" is replicable and safe due to the short exposure time for colour mapping needed to obtain satisfactory images.This would help establish their use as another strong prenatal predictor of important congenital heart disease, D-TGA, and other DD-lesions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".